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A High Performance Algorithm on Uncertainty Computing

In: Current Trends in High Performance Computing and Its Applications

Author

Listed:
  • Suixiang Shi

    (Northeastern University, School of Information Science & Engineering)

  • Qing Li

    (Shanghai University, School of Computer Science & Engineering)

  • Lingyu Xu

    (Shanghai University, School of Computer Science & Engineering)

  • Dengwei Xia

    (Northeastern University, School of Information Science & Engineering)

  • Xiufeng Xia

    (Northeastern University, School of Information Science & Engineering)

  • Ge Yu

    (Northeastern University, School of Information Science & Engineering)

Abstract

In this paper, we develop a high performance algorithm which is adapted to uncertainty computing and give a new combination rules coming from the D–S and supply a gap that Dempster ignoranced. The evidence sources are adapted in different cases. The credibility of the evidence changes along with the different focus element. So, we give various credibility for every focus element to increase precision. The new method improves the precision and gets rid of disconvergent answer.

Suggested Citation

  • Suixiang Shi & Qing Li & Lingyu Xu & Dengwei Xia & Xiufeng Xia & Ge Yu, 2005. "A High Performance Algorithm on Uncertainty Computing," Springer Books, in: Wu Zhang & Weiqin Tong & Zhangxin Chen & Roland Glowinski (ed.), Current Trends in High Performance Computing and Its Applications, pages 437-441, Springer.
    • Handle: RePEc:spr:sprchp:978-3-540-27912-9_58
    DOI: 10.1007/3-540-27912-1_58
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